65 citations · 135 across the 3 of their papers we have counts for
3 papers
Improving PWR core simulations by Monte Carlo uncertainty analysis and Bayesian inference
Emilio Castro, Carolina Ahnert, Oliver Buss +3
A Monte Carlo-based Bayesian inference model is applied to the prediction of reactor operation parameters of a PWR nuclear power plant. In this non-perturbative framework, high-dim…
MOCABA: a general Monte Carlo-Bayes procedure for improved predictions of integral functions of nuclear data
Axel Hoefer, Oliver Buss, Maik Hennebach +2
MOCABA is a combination of Monte Carlo sampling and Bayesian updating algorithms for the prediction of integral functions of nuclear data, such as reactor power distributions or ne…
Comparison of nuclear data uncertainty propagation methodologies for PWR burn-up simulations
Carlos Javier Diez, Oliver Buss, Axel Hoefer +2
Several methodologies using different levels of approximations have been developed for propagating nuclear data uncertainties in nuclear burn-up simulations. Most methods fall into…